Machine learning is a branch of artificial intelligence in which computer systems learn patterns from data to make predictions or decisions, rather than being explicitly programmed with fixed rules for every scenario. Instead of a developer writing rules for every possible situation, a machine learning model is trained on historical examples and learns to recognise patterns, which it then applies to new, unseen data. Generative AI and large language models are both built using machine learning techniques.
How machine learning works
A machine learning model is trained on a dataset of historical examples, gradually adjusting its internal parameters to improve its accuracy at a specific task, such as predicting which sales leads are likely to convert or detecting fraudulent transactions. Once trained, the model can apply what it learned to new data it has not seen before. AI Builder within Power Platform provides accessible tools for training simple custom machine learning models without requiring data science expertise.
How UK businesses use machine learning
- A sales team uses a custom AI Builder prediction model trained on historical deal data to score which current opportunities are most likely to close.
- A finance team uses machine learning-based anomaly detection to flag unusual transactions for review, drawing on patterns in historical data rather than fixed rules.
- A logistics business uses machine learning to forecast demand more accurately than simple historical averages, improving stock planning.
- A manufacturer uses machine learning to predict equipment maintenance needs based on sensor data, reducing unplanned downtime.
How Advantage applies machine learning for businesses
Advantage identifies practical machine learning opportunities within existing Power Platform and Dynamics 365 deployments, typically through AI Builder for accessible custom models, scaling to more advanced solutions where genuinely justified.
Frequently Asked Questions
What is the difference between machine learning and generative AI?
Machine learning is the broader field of training computer systems to learn patterns from data and make predictions or decisions. Generative AI is a more specific application of machine learning focused on creating new content. Most generative AI, including large language models, is built using machine learning techniques.
Does a business need data scientists to use machine learning?
Not always. Tools like AI Builder within Power Platform provide pre-built and guided custom machine learning models that business users can configure without data science expertise. More advanced or bespoke machine learning applications typically do benefit from specialist data science skills.
How much data is needed to train a useful machine learning model?
This varies significantly depending on the task. Pre-built models, such as those in AI Builder, require no training data from the business at all. Custom models built on a business's own data, such as a prediction model, can sometimes work with just a few hundred examples, though more data generally improves accuracy.
